Description Usage Arguments Value Examples

A simple R implementation of the phenograph [PhenoGraph](http://www.cell.com/cell/abstract/S0092-8674(15)00637-6) algorithm, which is a clustering method designed for high-dimensional single-cell data analysis. It works by creating a graph ("network") representing phenotypic similarities between cells by calculating the Jaccard coefficient between nearest-neighbor sets, and then identifying communities using the well known [Louvain method](https://sites.google.com/site/findcommunities/) in this graph.

1 | ```
runPhenograph(object, knn = 30, scale = FALSE, verbose = FALSE, ...)
``` |

`object` |
a CYT object. |

`knn` |
numeric. Number of nearest neighbours, default is 30. |

`scale` |
logical. Whether to scale the expression matrix |

`verbose` |
logical. Whether to print calculation progress. |

`...` |
Parameters passing to |

A CYT object with cluster

1 2 3 4 | ```
cyt.file <- system.file("extdata/cyt.rds", package = "CytoTree")
cyt <- readRDS(file = cyt.file)
cyt <- runPhenograph(cyt, knn = 30, verbose = TRUE)
``` |

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